KIUA2006 Use of AI and ML in biochemistry
- Course codeKIUA2006
- Number of credits10
- Teaching semester2026 Spring
- Language of instructionNorwegian
- CampusHamar
- Required prerequisite knowledge
None
This course delves into the intersection of artificial intelligence (AI) and biochemistry. The course is designed for students with a background in AI and ML and provides an introduction to chemistry and biochemistry, enabling students to build a bridge between the two fields. AI and ML have enabled chemists and biochemists to analyse enormous volumes of data, optimise chemical processes and design new molecules and materials more quickly and more accurately than before. Among other things, AI is expected to have a major impact on how drugs and materials are discovered, developed and manufactured and could, for example, streamline the development of vaccines, as well as identification of possible adverse effects and production processes. The course covers the following topics:
- Atoms, molecules and the most important substance classes in organic chemistry
- Chemical bonds, molecular geometry and intermolecular forces
- Chemical reactions and chemical equilibrium
- Acids and bases
- Nucleic acids, replication, transcription, translation, amino acids and proteins
- The three-dimensional structure and function of proteins in the cell
- Enzymes, enzyme kinetics and regulation
- Structure of biological membranes
- Principles of energy metabolism in cells
- Computational chemistry and modelling
- Use of AI and ML in biochemistry
Learning Outcome
Upon successfully passing the course, students will have achieved the following learning outcomes:
The student will have
- knowledge of basic concepts and theory in chemistry and biochemistry
- knowledge of calculations in connection with chemical reactions
- knowledge of the chemical composition of substances and the most important forms of chemical bonds and forces
- knowledge of the different substance classes in organic chemistry. This includes their structure and functional groups, isomerism, nomenclature and certain reactions
- knowledge of the structure and properties of important macromolecules
- knowledge of different reaction cycles and reaction pathways and is able to explain their purpose
- knowledge of the structure and importance of enzymes as catalysts for biological reactions, as well as regulatory mechanisms for enzymes
- knowledge of deep learning algorithms and their applications in the analysis of protein structures, protein folding and functional genomics
- knowledge of molecular modelling and algorithms for homology modelling
- knowledge of how AI and ML are expected to affect knowledge generation and working methods in biochemistry and adjacent fields
The student will be able to
- use AI and ML as tools to perform calculations and solve complex tasks in biochemistry and adjacent fields
- perform pre-processing of data and use ML algorithms to predict protein structures and genomics analyses.
- use AI to predict molecular interactions, identify potential drug candidates and optimise drug properties.
- use techniques to integrate different data sources such as genomics, proteomics and metabolomics in order to gain comprehensive insights into complex biological systems.
- use fundamental nomenclature, name and write formulas for simple compounds and describe the structure and properties of organic substances and will also have an overview of certain reactions
- convert units of measurement linked to mass, volume, temperature, amount of substance and concentration
- balance chemical reaction equations and perform calculations in connection with chemical reactions and chemical solutions
The student will be able to
- use their AI and ML skills to solve challenges in chemistry and biochemistry
- exchange views and experiences relating to AI challenges in chemistry and biochemistry with others
- communicate key subject matter relating to AI and ML in writing in Norwegian
- acquire new knowledge linked to the topics addressed on the course and seek and accept supervision
- discuss ethical issues relating to AI in biochemistry, including privacy and responsible research practices, as well as regulatory frameworks for AI-driven biotechnology in line with good practices for information and source criticism
- communicate selected central laboratory methods used in chemistry and biochemistry
The course comprises a combination of lectures, practical exercises and demonstrations in the laboratory, independent study and academic supervision.
- participation in teaching and laboratory exercises in accordance with the teaching plan
Compulsory coursework requirements that have been passed are valid for 12 months only. Students wishing to take examinations after 12 months must pass the compulsory coursework requirements again in connection with the next scheduled delivery of the course.
| Form of assessment | Grading scale | Grouping | Duration of assessment | Support materials | Proportion | Comment |
|---|---|---|---|---|---|---|
Written examination with invigilation | ECTS - A-F | Individual | 4 Hour(s) |
| 100 |
- 4-hour invigilated individual written examination
The assignment is assessed using a grading scale from A-F, where E is the lowest passing grade.
Students are able to choose which language to use for their examination. The available options are Norwegian Bokmål, Nynorsk and English.
Permitted aids:
- None